Triple
T15521468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristalina Georgieva |
E368977
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Kristalina |
E368977
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kristalina | Statement: [Kristalina Georgieva, givenName, Kristalina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kristalina Context triple: [Kristalina Georgieva, givenName, Kristalina]
-
A.
Kristalina
chosen
Kristalina is the first name of Kristalina Georgieva, a Bulgarian economist and the Managing Director of the International Monetary Fund.
-
B.
Maria Kanova
Maria Kanova was the wife of German novelist Heinrich Mann, associated with his later life and exile period.
-
C.
Katherine Tsina
Katherine Tsina is an American artist and designer best known as the wife of musician Andrew Bird and for her work in visual arts and fashion.
-
D.
Kristina
Kristina is a feminine given name commonly used in various European countries, often considered a variant of Christina.
-
E.
Ekaterina Gradova
Ekaterina Gradova was a Soviet and Russian actress best known for her roles in popular 1970s film and television productions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85a1794cc8190b0b428716296e63e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0403543188190abac49d2b9decb89 |
completed | April 16, 2026, 1:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d54ea5c8190b3b220ad10ba8f40 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 4:04 a.m.